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<div class="title">correspondence_estimation_normal_shooting.hpp</div>  </div>
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<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">/*</span></div>
<div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment"> * Software License Agreement (BSD License)</span></div>
<div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> *  Point Cloud Library (PCL) - www.pointclouds.org</span></div>
<div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> *  Copyright (c) 2010-2012, Willow Garage, Inc.</span></div>
<div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment"> *  Copyright (c) 2012-, Open Perception, Inc.</span></div>
<div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="comment"> *  All rights reserved.</span></div>
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<div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="comment"> *  modification, are permitted provided that the following conditions</span></div>
<div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="comment"> *  are met:</span></div>
<div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="comment"> *   * Redistributions of source code must retain the above copyright</span></div>
<div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="comment"> *     notice, this list of conditions and the following disclaimer.</span></div>
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<div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;<span class="comment"> * $Id$</span></div>
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<div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;<span class="comment"> */</span></div>
<div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;<span class="preprocessor">#ifndef PCL_REGISTRATION_IMPL_CORRESPONDENCE_ESTIMATION_NORMAL_SHOOTING_H_</span></div>
<div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;<span class="preprocessor">#define PCL_REGISTRATION_IMPL_CORRESPONDENCE_ESTIMATION_NORMAL_SHOOTING_H_</span></div>
<div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160; </div>
<div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;<span class="preprocessor">#include &lt;pcl/common/copy_point.h&gt;</span></div>
<div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160; </div>
<div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>Source, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>Target, <span class="keyword">typename</span> NormalT, <span class="keyword">typename</span> Scalar&gt; <span class="keywordtype">bool</span></div>
<div class="line"><a name="l00047"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#af979935c7f43038ab68ad6d0d701a801">   47</a></span>&#160;<a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#af979935c7f43038ab68ad6d0d701a801">pcl::registration::CorrespondenceEstimationNormalShooting&lt;PointSource, PointTarget, NormalT, Scalar&gt;::initCompute</a> ()</div>
<div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;{</div>
<div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;  <span class="keywordflow">if</span> (!source_normals_)</div>
<div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;  {</div>
<div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;    PCL_WARN (<span class="stringliteral">&quot;[pcl::registration::%s::initCompute] Datasets containing normals for source have not been given!\n&quot;</span>, getClassName ().c_str ());</div>
<div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;    <span class="keywordflow">return</span> (<span class="keyword">false</span>);</div>
<div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;  }</div>
<div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160; </div>
<div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;  <span class="keywordflow">return</span> (<a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html">CorrespondenceEstimationBase&lt;PointSource, PointTarget, Scalar&gt;::initCompute</a> ());</div>
<div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;}</div>
<div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160; </div>
<div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>Source, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>Target, <span class="keyword">typename</span> NormalT, <span class="keyword">typename</span> Scalar&gt; <span class="keywordtype">void</span></div>
<div class="line"><a name="l00060"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a348a50a8b8a0d3c5b14704d283ce068c">   60</a></span>&#160;<a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a348a50a8b8a0d3c5b14704d283ce068c">pcl::registration::CorrespondenceEstimationNormalShooting&lt;PointSource, PointTarget, NormalT, Scalar&gt;::determineCorrespondences</a> (</div>
<div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;    pcl::Correspondences &amp;correspondences, <span class="keywordtype">double</span> max_distance)</div>
<div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;{</div>
<div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;  <span class="keywordflow">if</span> (!initCompute ())</div>
<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160; </div>
<div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;  correspondences.resize (indices_-&gt;size ());</div>
<div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160; </div>
<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;  std::vector&lt;int&gt; nn_indices (k_);</div>
<div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;  std::vector&lt;float&gt; nn_dists (k_);</div>
<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160; </div>
<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;  <span class="keywordtype">double</span> min_dist = std::numeric_limits&lt;double&gt;::max ();</div>
<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;  <span class="keywordtype">int</span> min_index = 0;</div>
<div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;  </div>
<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;  <a class="code" href="structpcl_1_1_correspondence.html">pcl::Correspondence</a> corr;</div>
<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> nr_valid_correspondences = 0;</div>
<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160; </div>
<div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;  <span class="comment">// Check if the template types are the same. If true, avoid a copy.</span></div>
<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;  <span class="comment">// Both point types MUST be registered using the POINT_CLOUD_REGISTER_POINT_STRUCT macro!</span></div>
<div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;  <span class="keywordflow">if</span> (isSamePointType&lt;PointSource, PointTarget&gt; ())</div>
<div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;  {</div>
<div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;    PointTarget pt;</div>
<div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;    <span class="comment">// Iterate over the input set of source indices</span></div>
<div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;    <span class="keywordflow">for</span> (std::vector&lt;int&gt;::const_iterator idx_i = indices_-&gt;begin (); idx_i != indices_-&gt;end (); ++idx_i)</div>
<div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;    {</div>
<div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;      tree_-&gt;nearestKSearch (input_-&gt;points[*idx_i], k_, nn_indices, nn_dists);</div>
<div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160; </div>
<div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;      <span class="comment">// Among the K nearest neighbours find the one with minimum perpendicular distance to the normal</span></div>
<div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;      min_dist = std::numeric_limits&lt;double&gt;::max ();</div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;      </div>
<div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;      <span class="comment">// Find the best correspondence</span></div>
<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> j = 0; j &lt; nn_indices.size (); j++)</div>
<div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;      {</div>
<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;        <span class="comment">// computing the distance between a point and a line in 3d. </span></div>
<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;        <span class="comment">// Reference - http://mathworld.wolfram.com/Point-LineDistance3-Dimensional.html</span></div>
<div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;        pt.x = target_-&gt;points[nn_indices[j]].x - input_-&gt;points[*idx_i].x;</div>
<div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;        pt.y = target_-&gt;points[nn_indices[j]].y - input_-&gt;points[*idx_i].y;</div>
<div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;        pt.z = target_-&gt;points[nn_indices[j]].z - input_-&gt;points[*idx_i].z;</div>
<div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160; </div>
<div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;        <span class="keyword">const</span> <a class="code" href="structpcl_1_1_normal.html">NormalT</a> &amp;normal = source_normals_-&gt;points[*idx_i];</div>
<div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;        Eigen::Vector3d N (normal.normal_x, normal.normal_y, normal.normal_z);</div>
<div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;        Eigen::Vector3d V (pt.x, pt.y, pt.z);</div>
<div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;        Eigen::Vector3d C = N.cross (V);</div>
<div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;        </div>
<div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;        <span class="comment">// Check if we have a better correspondence</span></div>
<div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;        <span class="keywordtype">double</span> dist = C.dot (C);</div>
<div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;        <span class="keywordflow">if</span> (dist &lt; min_dist)</div>
<div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;        {</div>
<div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;          min_dist = dist;</div>
<div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;          min_index = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (j);</div>
<div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;        }</div>
<div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;      }</div>
<div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;      <span class="keywordflow">if</span> (min_dist &gt; max_distance)</div>
<div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;        <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160; </div>
<div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;      corr.<a class="code" href="structpcl_1_1_correspondence.html#a1c5d6554ca02dd7aa34fa02f346e7399">index_query</a> = *idx_i;</div>
<div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;      corr.<a class="code" href="structpcl_1_1_correspondence.html#a5e5d2178826d203a755d37bfd317d701">index_match</a> = nn_indices[min_index];</div>
<div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;      corr.distance = nn_dists[min_index];<span class="comment">//min_dist;</span></div>
<div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;      correspondences[nr_valid_correspondences++] = corr;</div>
<div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;    }</div>
<div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;  }</div>
<div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;  {</div>
<div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;    PointTarget pt;</div>
<div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;    </div>
<div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;    <span class="comment">// Iterate over the input set of source indices</span></div>
<div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;    <span class="keywordflow">for</span> (std::vector&lt;int&gt;::const_iterator idx_i = indices_-&gt;begin (); idx_i != indices_-&gt;end (); ++idx_i)</div>
<div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;    {</div>
<div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;      tree_-&gt;nearestKSearch (input_-&gt;points[*idx_i], k_, nn_indices, nn_dists);</div>
<div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160; </div>
<div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;      <span class="comment">// Among the K nearest neighbours find the one with minimum perpendicular distance to the normal</span></div>
<div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;      min_dist = std::numeric_limits&lt;double&gt;::max ();</div>
<div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;      </div>
<div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;      <span class="comment">// Find the best correspondence</span></div>
<div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> j = 0; j &lt; nn_indices.size (); j++)</div>
<div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;      {</div>
<div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;        PointSource pt_src;</div>
<div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;        <span class="comment">// Copy the source data to a target PointTarget format so we can search in the tree</span></div>
<div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;        <a class="code" href="group__common.html#gab978bf1754771246b2f140a5b52a8f8b">copyPoint</a> (input_-&gt;points[*idx_i], pt_src);</div>
<div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160; </div>
<div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;        <span class="comment">// computing the distance between a point and a line in 3d. </span></div>
<div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;        <span class="comment">// Reference - http://mathworld.wolfram.com/Point-LineDistance3-Dimensional.html</span></div>
<div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;        pt.x = target_-&gt;points[nn_indices[j]].x - pt_src.x;</div>
<div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;        pt.y = target_-&gt;points[nn_indices[j]].y - pt_src.y;</div>
<div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;        pt.z = target_-&gt;points[nn_indices[j]].z - pt_src.z;</div>
<div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;        </div>
<div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;        <span class="keyword">const</span> <a class="code" href="structpcl_1_1_normal.html">NormalT</a> &amp;normal = source_normals_-&gt;points[*idx_i];</div>
<div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;        Eigen::Vector3d N (normal.normal_x, normal.normal_y, normal.normal_z);</div>
<div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;        Eigen::Vector3d V (pt.x, pt.y, pt.z);</div>
<div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;        Eigen::Vector3d C = N.cross (V);</div>
<div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;        </div>
<div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;        <span class="comment">// Check if we have a better correspondence</span></div>
<div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;        <span class="keywordtype">double</span> dist = C.dot (C);</div>
<div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;        <span class="keywordflow">if</span> (dist &lt; min_dist)</div>
<div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;        {</div>
<div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;          min_dist = dist;</div>
<div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;          min_index = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (j);</div>
<div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;        }</div>
<div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;      }</div>
<div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;      <span class="keywordflow">if</span> (min_dist &gt; max_distance)</div>
<div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;        <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;      </div>
<div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;      corr.<a class="code" href="structpcl_1_1_correspondence.html#a1c5d6554ca02dd7aa34fa02f346e7399">index_query</a> = *idx_i;</div>
<div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;      corr.<a class="code" href="structpcl_1_1_correspondence.html#a5e5d2178826d203a755d37bfd317d701">index_match</a> = nn_indices[min_index];</div>
<div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;      corr.distance = nn_dists[min_index];<span class="comment">//min_dist;</span></div>
<div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;      correspondences[nr_valid_correspondences++] = corr;</div>
<div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;    }</div>
<div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;  }</div>
<div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;  correspondences.resize (nr_valid_correspondences);</div>
<div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;  deinitCompute ();</div>
<div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;}</div>
<div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160; </div>
<div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>Source, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>Target, <span class="keyword">typename</span> NormalT, <span class="keyword">typename</span> Scalar&gt; <span class="keywordtype">void</span></div>
<div class="line"><a name="l00174"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a93c946684ceff4a5686852be95852835">  174</a></span>&#160;<a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a93c946684ceff4a5686852be95852835">pcl::registration::CorrespondenceEstimationNormalShooting&lt;PointSource, PointTarget, NormalT, Scalar&gt;::determineReciprocalCorrespondences</a> (</div>
<div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;    pcl::Correspondences &amp;correspondences, <span class="keywordtype">double</span> max_distance)</div>
<div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;{</div>
<div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;  <span class="keywordflow">if</span> (!initCompute ())</div>
<div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160; </div>
<div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;  <span class="comment">// setup tree for reciprocal search</span></div>
<div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;  <span class="comment">// Set the internal point representation of choice</span></div>
<div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;  <span class="keywordflow">if</span> (!initComputeReciprocal ())</div>
<div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160; </div>
<div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;  correspondences.resize (indices_-&gt;size ());</div>
<div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160; </div>
<div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;  std::vector&lt;int&gt; nn_indices (k_);</div>
<div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;  std::vector&lt;float&gt; nn_dists (k_);</div>
<div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;  std::vector&lt;int&gt; index_reciprocal (1);</div>
<div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;  std::vector&lt;float&gt; distance_reciprocal (1);</div>
<div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160; </div>
<div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;  <span class="keywordtype">double</span> min_dist = std::numeric_limits&lt;double&gt;::max ();</div>
<div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;  <span class="keywordtype">int</span> min_index = 0;</div>
<div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;  </div>
<div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;  <a class="code" href="structpcl_1_1_correspondence.html">pcl::Correspondence</a> corr;</div>
<div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> nr_valid_correspondences = 0;</div>
<div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;  <span class="keywordtype">int</span> target_idx = 0;</div>
<div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160; </div>
<div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;  <span class="comment">// Check if the template types are the same. If true, avoid a copy.</span></div>
<div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;  <span class="comment">// Both point types MUST be registered using the POINT_CLOUD_REGISTER_POINT_STRUCT macro!</span></div>
<div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;  <span class="keywordflow">if</span> (isSamePointType&lt;PointSource, PointTarget&gt; ())</div>
<div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;  {</div>
<div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;    PointTarget pt;</div>
<div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;    <span class="comment">// Iterate over the input set of source indices</span></div>
<div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;    <span class="keywordflow">for</span> (std::vector&lt;int&gt;::const_iterator idx_i = indices_-&gt;begin (); idx_i != indices_-&gt;end (); ++idx_i)</div>
<div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;    {</div>
<div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;      tree_-&gt;nearestKSearch (input_-&gt;points[*idx_i], k_, nn_indices, nn_dists);</div>
<div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160; </div>
<div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;      <span class="comment">// Among the K nearest neighbours find the one with minimum perpendicular distance to the normal</span></div>
<div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;      min_dist = std::numeric_limits&lt;double&gt;::max ();</div>
<div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;      </div>
<div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;      <span class="comment">// Find the best correspondence</span></div>
<div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> j = 0; j &lt; nn_indices.size (); j++)</div>
<div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;      {</div>
<div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;        <span class="comment">// computing the distance between a point and a line in 3d. </span></div>
<div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;        <span class="comment">// Reference - http://mathworld.wolfram.com/Point-LineDistance3-Dimensional.html</span></div>
<div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;        pt.x = target_-&gt;points[nn_indices[j]].x - input_-&gt;points[*idx_i].x;</div>
<div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;        pt.y = target_-&gt;points[nn_indices[j]].y - input_-&gt;points[*idx_i].y;</div>
<div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;        pt.z = target_-&gt;points[nn_indices[j]].z - input_-&gt;points[*idx_i].z;</div>
<div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160; </div>
<div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;        <span class="keyword">const</span> <a class="code" href="structpcl_1_1_normal.html">NormalT</a> &amp;normal = source_normals_-&gt;points[*idx_i];</div>
<div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;        Eigen::Vector3d N (normal.normal_x, normal.normal_y, normal.normal_z);</div>
<div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;        Eigen::Vector3d V (pt.x, pt.y, pt.z);</div>
<div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;        Eigen::Vector3d C = N.cross (V);</div>
<div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;        </div>
<div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;        <span class="comment">// Check if we have a better correspondence</span></div>
<div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;        <span class="keywordtype">double</span> dist = C.dot (C);</div>
<div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;        <span class="keywordflow">if</span> (dist &lt; min_dist)</div>
<div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;        {</div>
<div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;          min_dist = dist;</div>
<div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;          min_index = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (j);</div>
<div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;        }</div>
<div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;      }</div>
<div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;      <span class="keywordflow">if</span> (min_dist &gt; max_distance)</div>
<div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;        <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160; </div>
<div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;      <span class="comment">// Check if the correspondence is reciprocal</span></div>
<div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;      target_idx = nn_indices[min_index];</div>
<div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;      tree_reciprocal_-&gt;nearestKSearch (target_-&gt;points[target_idx], 1, index_reciprocal, distance_reciprocal);</div>
<div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160; </div>
<div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;      <span class="keywordflow">if</span> (*idx_i != index_reciprocal[0])</div>
<div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;        <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160; </div>
<div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;      <span class="comment">// Correspondence IS reciprocal, save it and continue</span></div>
<div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;      corr.<a class="code" href="structpcl_1_1_correspondence.html#a1c5d6554ca02dd7aa34fa02f346e7399">index_query</a> = *idx_i;</div>
<div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;      corr.<a class="code" href="structpcl_1_1_correspondence.html#a5e5d2178826d203a755d37bfd317d701">index_match</a> = nn_indices[min_index];</div>
<div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;      corr.distance = nn_dists[min_index];<span class="comment">//min_dist;</span></div>
<div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;      correspondences[nr_valid_correspondences++] = corr;</div>
<div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;    }</div>
<div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;  }</div>
<div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;  {</div>
<div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;    PointTarget pt;</div>
<div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;    </div>
<div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;    <span class="comment">// Iterate over the input set of source indices</span></div>
<div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;    <span class="keywordflow">for</span> (std::vector&lt;int&gt;::const_iterator idx_i = indices_-&gt;begin (); idx_i != indices_-&gt;end (); ++idx_i)</div>
<div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;    {</div>
<div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;      tree_-&gt;nearestKSearch (input_-&gt;points[*idx_i], k_, nn_indices, nn_dists);</div>
<div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160; </div>
<div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;      <span class="comment">// Among the K nearest neighbours find the one with minimum perpendicular distance to the normal</span></div>
<div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160;      min_dist = std::numeric_limits&lt;double&gt;::max ();</div>
<div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160;      </div>
<div class="line"><a name="l00263"></a><span class="lineno">  263</span>&#160;      <span class="comment">// Find the best correspondence</span></div>
<div class="line"><a name="l00264"></a><span class="lineno">  264</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> j = 0; j &lt; nn_indices.size (); j++)</div>
<div class="line"><a name="l00265"></a><span class="lineno">  265</span>&#160;      {</div>
<div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;        PointSource pt_src;</div>
<div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;        <span class="comment">// Copy the source data to a target PointTarget format so we can search in the tree</span></div>
<div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160;        <a class="code" href="group__common.html#gab978bf1754771246b2f140a5b52a8f8b">copyPoint</a> (input_-&gt;points[*idx_i], pt_src);</div>
<div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160; </div>
<div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;        <span class="comment">// computing the distance between a point and a line in 3d. </span></div>
<div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160;        <span class="comment">// Reference - http://mathworld.wolfram.com/Point-LineDistance3-Dimensional.html</span></div>
<div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;        pt.x = target_-&gt;points[nn_indices[j]].x - pt_src.x;</div>
<div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160;        pt.y = target_-&gt;points[nn_indices[j]].y - pt_src.y;</div>
<div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;        pt.z = target_-&gt;points[nn_indices[j]].z - pt_src.z;</div>
<div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160;        </div>
<div class="line"><a name="l00276"></a><span class="lineno">  276</span>&#160;        <span class="keyword">const</span> <a class="code" href="structpcl_1_1_normal.html">NormalT</a> &amp;normal = source_normals_-&gt;points[*idx_i];</div>
<div class="line"><a name="l00277"></a><span class="lineno">  277</span>&#160;        Eigen::Vector3d N (normal.normal_x, normal.normal_y, normal.normal_z);</div>
<div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;        Eigen::Vector3d V (pt.x, pt.y, pt.z);</div>
<div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;        Eigen::Vector3d C = N.cross (V);</div>
<div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160;        </div>
<div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;        <span class="comment">// Check if we have a better correspondence</span></div>
<div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160;        <span class="keywordtype">double</span> dist = C.dot (C);</div>
<div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;        <span class="keywordflow">if</span> (dist &lt; min_dist)</div>
<div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;        {</div>
<div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160;          min_dist = dist;</div>
<div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;          min_index = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (j);</div>
<div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;        }</div>
<div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160;      }</div>
<div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;      <span class="keywordflow">if</span> (min_dist &gt; max_distance)</div>
<div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;        <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160; </div>
<div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;      <span class="comment">// Check if the correspondence is reciprocal</span></div>
<div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160;      target_idx = nn_indices[min_index];</div>
<div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160;      tree_reciprocal_-&gt;nearestKSearch (target_-&gt;points[target_idx], 1, index_reciprocal, distance_reciprocal);</div>
<div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160; </div>
<div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;      <span class="keywordflow">if</span> (*idx_i != index_reciprocal[0])</div>
<div class="line"><a name="l00297"></a><span class="lineno">  297</span>&#160;        <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00298"></a><span class="lineno">  298</span>&#160; </div>
<div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160;      <span class="comment">// Correspondence IS reciprocal, save it and continue</span></div>
<div class="line"><a name="l00300"></a><span class="lineno">  300</span>&#160;      corr.<a class="code" href="structpcl_1_1_correspondence.html#a1c5d6554ca02dd7aa34fa02f346e7399">index_query</a> = *idx_i;</div>
<div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;      corr.<a class="code" href="structpcl_1_1_correspondence.html#a5e5d2178826d203a755d37bfd317d701">index_match</a> = nn_indices[min_index];</div>
<div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;      corr.distance = nn_dists[min_index];<span class="comment">//min_dist;</span></div>
<div class="line"><a name="l00303"></a><span class="lineno">  303</span>&#160;      correspondences[nr_valid_correspondences++] = corr;</div>
<div class="line"><a name="l00304"></a><span class="lineno">  304</span>&#160;    }</div>
<div class="line"><a name="l00305"></a><span class="lineno">  305</span>&#160;  }</div>
<div class="line"><a name="l00306"></a><span class="lineno">  306</span>&#160;  correspondences.resize (nr_valid_correspondences);</div>
<div class="line"><a name="l00307"></a><span class="lineno">  307</span>&#160;  deinitCompute ();</div>
<div class="line"><a name="l00308"></a><span class="lineno">  308</span>&#160;}</div>
<div class="line"><a name="l00309"></a><span class="lineno">  309</span>&#160; </div>
<div class="line"><a name="l00310"></a><span class="lineno">  310</span>&#160;<span class="preprocessor">#endif    </span><span class="comment">// PCL_REGISTRATION_IMPL_CORRESPONDENCE_ESTIMATION_NORMAL_SHOOTING_H_</span></div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_correspondence_estimation_base_html"><div class="ttname"><a href="classpcl_1_1registration_1_1_correspondence_estimation_base.html">pcl::registration::CorrespondenceEstimationBase</a></div><div class="ttdoc">Abstract CorrespondenceEstimationBase class. All correspondence estimation methods should inherit fro...</div><div class="ttdef"><b>Definition:</b> correspondence_estimation.h:64</div></div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_correspondence_estimation_normal_shooting_html_a348a50a8b8a0d3c5b14704d283ce068c"><div class="ttname"><a href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a348a50a8b8a0d3c5b14704d283ce068c">pcl::registration::CorrespondenceEstimationNormalShooting::determineCorrespondences</a></div><div class="ttdeci">void determineCorrespondences(pcl::Correspondences &amp;correspondences, double max_distance=std::numeric_limits&lt; double &gt;::max())</div><div class="ttdoc">Determine the correspondences between input and target cloud.</div><div class="ttdef"><b>Definition:</b> correspondence_estimation_normal_shooting.hpp:60</div></div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_correspondence_estimation_normal_shooting_html_a93c946684ceff4a5686852be95852835"><div class="ttname"><a href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a93c946684ceff4a5686852be95852835">pcl::registration::CorrespondenceEstimationNormalShooting::determineReciprocalCorrespondences</a></div><div class="ttdeci">virtual void determineReciprocalCorrespondences(pcl::Correspondences &amp;correspondences, double max_distance=std::numeric_limits&lt; double &gt;::max())</div><div class="ttdoc">Determine the reciprocal correspondences between input and target cloud. A correspondence is consider...</div><div class="ttdef"><b>Definition:</b> correspondence_estimation_normal_shooting.hpp:174</div></div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_correspondence_estimation_normal_shooting_html_af979935c7f43038ab68ad6d0d701a801"><div class="ttname"><a href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#af979935c7f43038ab68ad6d0d701a801">pcl::registration::CorrespondenceEstimationNormalShooting::initCompute</a></div><div class="ttdeci">bool initCompute()</div><div class="ttdoc">Internal computation initalization.</div><div class="ttdef"><b>Definition:</b> correspondence_estimation_normal_shooting.hpp:47</div></div>
<div class="ttc" id="agroup__common_html_gab978bf1754771246b2f140a5b52a8f8b"><div class="ttname"><a href="group__common.html#gab978bf1754771246b2f140a5b52a8f8b">pcl::copyPoint</a></div><div class="ttdeci">void copyPoint(const PointInT &amp;point_in, PointOutT &amp;point_out)</div><div class="ttdoc">Copy the fields of a source point into a target point.</div><div class="ttdef"><b>Definition:</b> copy_point.hpp:138</div></div>
<div class="ttc" id="astructpcl_1_1_correspondence_html"><div class="ttname"><a href="structpcl_1_1_correspondence.html">pcl::Correspondence</a></div><div class="ttdoc">Correspondence represents a match between two entities (e.g., points, descriptors,...</div><div class="ttdef"><b>Definition:</b> correspondence.h:59</div></div>
<div class="ttc" id="astructpcl_1_1_correspondence_html_a1c5d6554ca02dd7aa34fa02f346e7399"><div class="ttname"><a href="structpcl_1_1_correspondence.html#a1c5d6554ca02dd7aa34fa02f346e7399">pcl::Correspondence::index_query</a></div><div class="ttdeci">int index_query</div><div class="ttdoc">Index of the query (source) point.</div><div class="ttdef"><b>Definition:</b> correspondence.h:61</div></div>
<div class="ttc" id="astructpcl_1_1_correspondence_html_a5e5d2178826d203a755d37bfd317d701"><div class="ttname"><a href="structpcl_1_1_correspondence.html#a5e5d2178826d203a755d37bfd317d701">pcl::Correspondence::index_match</a></div><div class="ttdeci">int index_match</div><div class="ttdoc">Index of the matching (target) point. Set to -1 if no correspondence found.</div><div class="ttdef"><b>Definition:</b> correspondence.h:63</div></div>
<div class="ttc" id="astructpcl_1_1_normal_html"><div class="ttname"><a href="structpcl_1_1_normal.html">pcl::Normal</a></div><div class="ttdoc">A point structure representing normal coordinates and the surface curvature estimate....</div><div class="ttdef"><b>Definition:</b> point_types.hpp:779</div></div>
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